Air-Cooling and Heating Systemfor Tiger in Zoo using Earth Tube Heat Exchanger

A specially designed air-cooling (and heating) system using Earth Tube Heat Exchanger (ETHE) was installed in the dwelling of a 15-year old white tiger (Panthera tigris) named Mahesh at Kamala Nehru Zoological Garden, Ahmedabad (India) in October 2000. This was done to alleviate the stresses experienced by Mahesh in summer, which is long and hot; and in winter nights, which can be quite cold. Summer temperatures in Ahmedabad remain around 40oC for a long time and can reach as high as 45oC. Night temperatures in winter can drop to 10oC or below. The system does both--provide cooling in summer and warming in winter. In winter the system warms up the ambient (cold) air by as much as 10oC at night. In summer the system cools the ambient (hot) air also by as much as 8 - 10oC during the day.

Bioelectricity Production and Comparative Evaluation of Electrode Materials in Microbial Fuel Cells Using Indigenous Anode-Reducing Bacterial Community From Wastewater of Rice-Based Industries

Microbial fuel cells (MFCs) are the electrochemical systems that harness the electricity production capacity of certain microbes from the reduction of biodegradable compounds. The present study aimed to develop mediator-less MFC without using expensive proton exchange membrane. In the present study, a triplicate of dual-chamber, mediator-less MFCs was operated with two local rice based industrial wastewater to explore the potential of this wastewater as a fuel option in these electrochemical systems. 30 combinations of 6 electrodes viz. Carbon (14 cm × 1.5 cm), Zn (14.9 cm × 4.9 cm), Cu (14.9 cm × 4.9 cm), Sn (14.1cm × 4.5cm), Fe (14cm × 4cm) and Al (14cm × 4.5 cm) were evaluated for each of the wastewater samples. Zn-C as anode-cathode combination produced a maximum voltage that was 1.084±0.016V and 1.086±0.028 and current of 1.777±0.115mA and 1.503±0.120 for KRM and SSR, respectively. In the present study, thick biofilm has been observed growing in MFC anode. Total 14 bacterial isolates growing in anode were obtained from two of the wastewater. The dual chambered, membrane-less and mediator-less MFCs were employed successfully to improve the economic feasibility of these electrochemical systems to generate bioelectricity and wastewater treatment simultaneously.Keywords: Membrane-less, Microbial Fuel Cells, Biofilm, Wastewater, Electrogenic.Article History: Received June 25th 2016; Received in revised form Dec 15th 2016; Accepted January 5th 2017; Available onlineHow to Cite This Article: Reena, M. and Jadhav, S. K. (2017) Bioelectricity production and Comparative Evaluation of Electrode Materials in Microbial Fuel Cells using Indigenous Anode-reducing Bacterial Community from Wastewater of Rice-based Industries. International Journal of Renewable Energy Develeopment, 6(1), 83-92.http://dx.doi.org/10.14710/ijred.6.1.83-9

INFLUENCE OF METAL NITRATE TO FUEL RATIO ON THE MAGNETIC PROPERTIES OF NIFE2O4

Objective: Nickel ferrite nanoparticles with dimensions below 30 nm have been synthesized by sol-gel auto-combustion process. The nitrate-citrate gels were prepared from metal nitrates and citric acid solutions under various molar ratios of the metal nitrate to citric acid of 1, 2, 3 4 and 5 by sol-gel process. The results showed that nitrate citrate gels exhibit a self propagating behaviour after ignition in air at room temperature. The ratio of nitrates to citric acid also affects the combustion process. The as-prepared powder was annealed at 5000C for 6 hrs. The phase composition and structural properties of the obtained samples are investigated by X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM). Analysis of the XRD patterns showed the presence of α-Fe2O3 phase and other refractions corresponding to cubic spinel structure. The lattice constant obtained from XRD data increases with metal nitrate to fuel (citric acid) ratio. PACS No: 75.50.Gg, 74.25.Ld, 43.35.C

Changes in biological productivity associated with Ningaloo Niño / Niña events in the southern subtropical Indian Ocean in recent decades

Using observations and long term simulations of an ocean-biogeochemical coupled model, we investigate the biological response in the southern subtropical Indian Ocean (SIO) associated with Ningaloo Niño and Niña events. Ningaloo events have large impact on sea surface temperature (SST) with positive SST anomalies (SSTA) seen off the west coast of Australia in southern SIO during Ningaloo Niño and negative anomalies during Niña events. Our results indicate that during the developing period of Ningaloo Niño, low chlorophyll anomaly appears near the southwest Australian coast concurrently with high SSTA and vice-versa during Niña, which alter the seasonal cycle of biological productivity. The difference in the spatiotemporal response of chlorophyll is due to the southward advection of Leeuwin current during these events. Increased frequency of Ningaloo Niño events associated with cold phase of Pacific Decadal Oscillation (PDO) resulted in anomalous decrease in productivity during Austral summer in the SIO in the recent decades

Synthesis and metal complexation of chiral 3-mono-or 3, 3-bis-allyl-2-hydroxypyrrolopyrazine-1, 4-diones

A novel synthesis of chiral cyclic hydroxamic acids (4, 6, 8 and 10) related to cyclodipeptides is described. The crucial reduction of the nitro group of the N-nitroacetyl derivatives of (S)-α-amino acid esters is brought about by zinc-aq. ammonium chloride. The FeIII and CuII complexes of one such cyclic hydroxamic acid 10a have been prepared and their DNAse activity investigated

Galactic `Snake' IRDC G11.11−-0.12: a site of multiple hub-filament systems and colliding filamentary clouds

To probe star formation processes, we present a multi-scale and multi-wavelength investigation of the `Snake' nebula/infrared dark cloud G11.11$-$0.12 (hereafter, G11; length $\sim$27 pc). Spitzer images hint at the presence of sub-filaments (in absorption), and reveal four infrared-dark hub-filament system (HFS) candidates (extent $<$ 6 pc) toward G11, where massive clumps ($>$ 500 $M_{\odot}$) and protostars are identified. The $^{13}$CO(2-1), C$^{18}$O(2-1), and NH$_{3}$(1,1) line data reveal a noticeable velocity oscillation toward G11, as well as its left part (or part-A) around V$_{lsr}$ of 31.5 km s$^{-1}$, and its right part (or part-B) around V$_{lsr}$ of 29.5 km s$^{-1}$. The common zone of these cloud components is investigated toward the center's G11 housing one HFS. Each cloud component hosts two sub-filaments. In comparison to part-A, more ATLASGAL clumps are observed toward part-B. The JWST near-infrared images discover one infrared-dark HFS candidate (extent $\sim$0.55 pc) around the massive protostar G11P1 (i.e., G11P1-HFS). Hence, the infrared observations reveal multiple infrared-dark HFS candidates at multi-scale in G11. The ALMA 1.16 mm continuum map shows multiple finger-like features (extent $\sim$3500-10000 AU) surrounding a dusty envelope-like feature (extent $\sim$18000 AU) toward the central hub of G11P1-HFS. Signatures of forming massive stars are found toward the center of the envelope-like feature. The ALMA H$^{13}$CO$^{+}$ line data show two cloud components with a velocity separation of $\sim$2 km s$^{-1}$ toward G11P1. Overall, the collision process, the ``fray and fragment'' mechanism, and the ``global non-isotropic collapse'' scenario seem to be operational in G11.Comment: 20 pages, 13 figures, 3 Tables, Accepted for publication in Monthly Notices of the Royal Astronomical Society (MNRAS) Journa

DEVELOPMENT AND VALIDATION OF UV SPECTROPHOTOMETRIC METHODS FOR DETERMINATION OF MEGLUMINE IN BULK

UV, first, second and third derivative spectrophotometric methods have been developed for the determination of meglumine. The solutions of standard and sample were prepared in distilled water. For the first method i.e. calibration curve UV spectrophotometric method, the quantitative determination of the drug was carried at 254 nm and the linearity range was found to be 10 – 60 µg/ml. For the first, second, third derivative spectrophotometric methods the drug was determined at 247 nm, 216 nm, 266 nm with the linearity range 10 – 60 µg /ml. The calibration graphs constructed at their wavelength of determination were found to be linear for UV and derivative spectrophotometric methods. All the proposed methods have been extensively validated. There was no significant difference between the performance of the proposed methods regarding the mean values and standard deviations

Automatic semantic segmentation and classification of remote sensing data for agriculture

Automatic semantic segmentation has expected increasing interest for researchers in recent years on multispectral remote sensing (RS) system. The agriculture supports 58 % of the population, in which 51 % of geographical area is under cultivation. Furthermore, the RS in agriculture can be used for identification, area estimation and monitoring, crop detection, soil mapping, crop yield modelling and production modelling etc. The RS images are high resolution images which can be used for agricultural and land cover classifications. Due to its high dimensional feature space, the conventional feature extraction techniques represent a progress of issues when handling huge size information e.g., computational cost, processing capacity and storage load. In order to overcome the existing drawback, we propose an automatic semantic segmentation without losing the significant data. In this paper, we use SOMs for segmentation purpose. Moreover, we proposed the particle swarm optimization technique (PSO) algorithm for finding cluster boundaries directly from the SOMs. On the other hand, we propose the deep residual network to achieve faster training process. Deep Residual Networks have been proved to be a very successful model on RS image classification. The main aim of this work is to achieve the overall accuracy greater than 85 % (OA > 85 %). So, we use a convolutional neural network (CNN), which outperforms better classification of certain crop types and yielding the target accuracies more than 85 % for all major crops. Furthermore, the proposed methods achieve good segmentation and classification accuracy than existing methods. The simulation results are further presented to show the performance of the proposed method applied to synthetic and real-world datasets

Exploring Population Dynamics in Nashik District: Applying Polynomial Extrapolation

In this study we have investigates the impact of polynomial degree selection on data fitting accuracy in analyzing population trends within Nashik District. Through a series of figures, it becomes evident that lower-degree polynomials, including linear and quadratic models, inadequately match the dataset's complexity. However, with escalating polynomial degrees, a notable improvement in fitting effectiveness emerges. This analysis highlights the critical role of selecting an appropriate polynomial degree in accurately representing underlying trends. While higher-degree polynomials offer improved fitting, the risk of overfitting, especially with smaller datasets, necessitates a delicate balance between complexity and accuracy. Understanding dataset characteristics is pivotal in determining the optimal polynomial degree for effective representation and prediction of population trends in Nashik District

Insecticide Resistance Management in Hybrid Cotton

Insecticide Resistance Management (IRM) strategies were demonstrated through area-wide farmer's participatory trials in fields of 11 farmers in Rohna Village (40 km from Nagpur) and fields of 21 farmers in Raulpally and Sankeypally villages in Ranga Reddy district in Andhra Pradesh (India), with hybrids MECH1.1, MECH.12 and RCH.2 in Ranga Reddy, and NHH.44 and Ankur 651 at Rohna